One-step synthesis of highly reduced graphene hydrogels for high power supercapacitor applications

Graphene hydrogels with high electrical conductivity were prepared by a one-step process using hydrazine hydrate as gel assembly agent (GH-HD). Conventional two-step process of gel formation and further reduction to prepare highly conducting gels was replaced by a single step involving equivalent amount of hydrazine. Optimized graphene oxide concentration was established to facilitate such monolith formation. Extensive characterization and control studies enabled understanding of the material properties and gel formation mechanism. The synthesized gel shows a high electrical conductivity of 1141 S/m. The supercapacitor based on GH-HD delivers a high specific capacitance of 190 F/g at a current density of 0.5 A/g and 123 F/g at very high current density of 100 A/g. Furthermore, excellent power capability and cyclic stability were also observed. 3D macroporous morphology of GH-HD makes it ideal for high rate supercapacitor applications

Ion Sieving Effects in Chemically Tuned Pillared Graphene Materials for Electrochemical Capacitors

Supercapacitors offer high power densities but require further improvements in energy densities for widespread commercial applications. In addition to the conventional strategy of using large surface area materials to enhance energy storage, recently, matching electrolyte ion sizes to material pore sizes has been shown to be particularly effective. However, synthesis and characterization of materials with precise pore sizes remain challenging. Herein, we propose to evaluate the layered structures in graphene derivatives as being analogous to pores and study the possibility of ion sieving. A class of pillared graphene based materials with suitable interlayer separation were synthesized, readily characterized by X-ray diffraction, and tested in various electrolytes. Electrochemical results show that the interlayer galleries could indeed sieve electrolyte ions based on size constrictions: ions with naked sizes that are smaller than the interlayer separation access the galleries, whereas the larger ions are restricted. These first observations of ion sieving in pillared graphene-based materials enable efficient charge storage through optimization of the d-spacing/ion size couple

Investigation of ion transport in chemically tuned pillared graphene materials through electrochemical impedance analysis

Chemically tuned pillared graphene structures show ability to limit restacking of graphene sheets for electrochemical energy storage in SCs. A comprehensive electrochemical characterization using various ion sizes allowed identification of ion-sieving in the cross-linked galleries of reduced pillared graphene materials (RPs). The access to the cross-linked galleries, which provide additional ion sorption sites, offered slightly increased capacitances in RPs compared to completely restacked sheets in reduced graphene oxide (RGO). We performed electrochemical impedance analyses on RPs and RGO to understand the ion transport inside the cross-linked graphene galleries. RGO adsorbs ions in the inter-particle micro/meso pores and the ion access to such sites from the bulk electrolyte occurs with relative ease. RPs sieve ions into their inter-layer gallery pores based on effective ion sizes and the ion transport process is resistive compared to RGO. A control study using 3D pillared graphene hydrogel with improved macro porosity assigns this resistive behavior and the moderate capacitances to limited ion access to the active sites due to excess number of pillars. The obtained results on the ion transport dynamics between graphene layers provide perspectives towards further optimization of these graphene materials for SCs

Sparsely Pillared Graphene Materials for High-Performance Supercapacitors: Improving Ion Transport and Storage Capacity

Graphene-based materials are extensively studied as promising candidates for supercapacitors (SCs) owing to the high surface area, electrical conductivity, and mechanical flexibility of graphene. Reduced graphene oxide (RGO), a close graphene-like material studied for SCs, offers limited specific capacitances (100 F·g–1) as the reduced graphene sheets partially restack through π–π interactions. This paper presents pillared graphene materials designed to minimize such graphitic restacking by cross-linking the graphene sheets with a bifunctional pillar molecule. Solid-state NMR, X-ray diffraction, and electrochemical analyses reveal that the synthesized materials possess covalently cross-linked graphene galleries that offer additional sites for ion sorption in SCs. Indeed, high specific capacitances in SCs are observed for the graphene materials synthesized with an optimized number of pillars. Specifically, the straightforward synthesis of a graphene hydrogel containing pillared structures and an interconnected porous network delivered a material with gravimetric capacitances two times greater than that of RGO (200 F·g–1vs 107 F·g–1) and volumetric capacitances that are nearly four times larger (210 F·cm–3vs 54 F·cm–3). Additionally, despite the presence of pillars inside the graphene galleries, the optimized materials show efficient ion transport characteristics. This work therefore brings perspectives for the next generation of high-performance SCs

AVID: An integrative framework for discovering functional relationships among proteins

BACKGROUND: Determining the functions of uncharacterized proteins is one of the most pressing problems in the post-genomic era. Large scale protein-protein interaction assays, global mRNA expression analyses and systematic protein localization studies provide experimental information that can be used for this purpose. The data from such experiments contain many false positives and false negatives, but can be processed using computational methods to provide reliable information about protein-protein relationships and protein function. An outstanding and important goal is to predict detailed functional annotation for all uncharacterized proteins that is reliable enough to effectively guide experiments. RESULTS: We present AVID, a computational method that uses a multi-stage learning framework to integrate experimental results with sequence information, generating networks reflecting functional similarities among proteins. We illustrate use of the networks by making predictions of detailed Gene Ontology (GO) annotations in three categories: molecular function, biological process, and cellular component. Applied to the yeast Saccharomyces cerevisiae, AVID provides 37,451 pair-wise functional linkages between 4,191 proteins. These relationships are ~65–78% accurate, as assessed by cross-validation testing. Assignments of highly detailed functional descriptors to proteins, based on the networks, are estimated to be ~67% accurate for GO categories describing molecular function and cellular component and ~52% accurate for terms describing biological process. The predictions cover 1,490 proteins with no previous annotation in GO and also assign more detailed functions to many proteins annotated only with less descriptive terms. Predictions made by AVID are largely distinct from those made by other methods. Out of 37,451 predicted pair-wise relationships, the greatest number shared in common with another method is 3,413. CONCLUSION: AVID provides three networks reflecting functional associations among proteins. We use these networks to generate new, highly detailed functional predictions for roughly half of the yeast proteome that are reliable enough to drive targeted experimental investigations. The predictions suggest many specific, testable hypotheses. All of the data are available as downloadable files as well as through an interactive website at . Thus, AVID will be a valuable resource for experimental biologists

Novel Application of Cyclolipopeptide Amphisin: Feasibility Study as Additive to Remediate Polycyclic Aromatic Hydrocarbon (PAH) Contaminated Sediments

To decontaminate dredged harbor sediments by bioremediation or electromigration processes, adding biosurfactants could enhance the bioavailability or mobility of contaminants in an aqueous phase. Pure amphisin from Pseudomonas fluorescens DSS73 displays increased effectiveness in releasing polycyclic aromatic hydrocarbons (PAHs) strongly adsorbed to sediments when compared to a synthetic anionic surfactant. Amphisin production by the bacteria in the natural environment was also considered. DSS73’s growth is weakened by three model PAHs above saturation, but amphisin is still produced. Estuarine water feeding the dredged material disposal site of a Norman harbor (France) allows both P. fluorescens DSS73 growth and amphisin production

Electrochemical control of supramolecular structures in solution and at the solid/liquid interface

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Model systems for flavoenzyme activity: flavin-functionalised SAMs as models for probing redox modulation through hydrogen bondingElectronic supplementary information (ESI) available: synthesis and spectroscopic details; cyclic voltammograms. See http://www.rsc.org/suppdata/cc/b3/b307980p/

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